在全球气候变化加剧与资源环境约束持续收紧的双重背景下，可持续发展已成为各国经济转型的核心共识，传统高耗能高排放的增长模式面临严峻挑战。中国作为全球制造业第一大国，制造业增加值占GDP比重长期保持在较高水平，同时也承担着较大的碳减排与环境治理压力。在双碳目标引领下，推动经济增长模式向绿色化数字化协同转型，成为破解制造业发展瓶颈、实现高质量发展的必然选择。数字化转型与绿色工艺创新的深度融合，不仅能够打破传统生产模式的路径依赖，更能构建技术—效率—生态三位一体的可持续生产体系，是制造业转型升级的关键突破口。本研究旨在揭示数字化技术对绿色工艺创新的驱动机制，为政府设计环境税制、碳市场机制等政策工具提供理论模型，优化“双碳”目标下产业转型的激励约束政策体系。并深入分析绿色工艺创新带给企业财务绩效与环境绩效的协同作用，指导其在工艺优化、设备升级等环节实现环境效益与经济效益的平衡决策。
Against the dual backdrop of intensifying global climate change and tightening resource and environmental
constraints, sustainable development has become a core consensus in the economic transformation of nations,
with the traditional high-energy, high-emission growth model facing severe challenges. As the world's largest
manufacturing country, China has long maintained a high proportion of manufacturing value-added in its GDP
while also bearing significant pressure for carbon emission reduction and environmental governance. Under the
guidance of the dual-carbon goals, promoting a green and digitalized collaborative transformation of the economic
growth model has become an inevitable choice to break through the bottlenecks in manufacturing development and
achieve high-quality growth. The deep integration of digital transformation and green process innovation can not
only break the path dependence of traditional production models but also establish a sustainable production system
integrating technology, efficiency, and ecology, serving as a key breakthrough for the transformation and upgrading
of the manufacturing industry. This study aims to reveal the driving mechanisms of digital technology on green
process innovation, providing a theoretical model for governments to design policy tools such as environmental
taxation systems and carbon market mechanisms, optimizing the incentive and constraint policy system for industrial
transformation under the dual-carbon goals. It also conducts an in-depth analysis of the synergistic effects of green
process innovation on corporate financial and environmental performance, guiding enterprises in achieving balanced
decisions on environmental and economic benefits in process optimization and equipment upgrades.
